Sample IRIS Competition

Organized by guyon - Current server time: Jan. 25, 2021, 11:46 a.m. UTC

Current

Development Phase
Nov. 15, 2018, midnight UTC

Next

Final Phase
April 30, 2050, midnight UTC

End

Competition Ends
Never

Solve Fisher's Famous Iris Problem

This competition is used in the M1 Projects A and B at Université Paris-Saclay. Do not enter if you are not part of that class.

This is the well known Iris dataset from Fisher's classic paper (Fisher, 1936). The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other.

References and credits:
R. A. Fisher. The use of multiple measurements in taxonomic problems. Annual Eugenics, 7, Part II, 179-188 (1936).
The competition protocol was designed by Isabelle Guyon.
The starting kit was adapted from an Jupyper notebook designed by Balazs Kegl.

Evaluation

The problem is a multiclass classification problem. Each sample (an Iris) is characterized by its sepal and petal width and length (4 features). You must predict the Iris categories: setosa, virginica, or versicolor.
You are given for training a data matrix X_train of dimension num_training_samples x num_features and an array y_train of labels of dimension num_training_samples. You must train a model which predicts the labels for two test matrices X_valid and X_test.
There are 2 phases:

  • Phase 1: development phase. We provide you with labeled training data and unlabeled validation and test data. Make predictions for both datasets. However, you will receive feed-back on your performance on the validation set only. The performance of your LAST submission will be displayed on the leaderboard.
  • Phase 2: final phase. You do not need to do anything. Your last submission of phase 1 will be automatically forwarded. Your performance on the test set will appear on the leaderboard when the organizers finish checking the submissions.

This sample competition allows you to submit either:

  • Only prediction results (no code).
  • A pre-trained prediction model.
  • A prediction model that must be trained and tested.

The submissions are evaluated using the accuracy metric.

Rules

Submissions must be made before the end of phase 1. You may submit 5 submissions every day and 100 in total.

This challenge is for educational purposes only and no prizes are granted. It is governed by the general ChaLearn contest rules.

Development Phase

Start: Nov. 15, 2018, midnight

Description: Development phase: tune your models and submit prediction results, trained model, or untrained model.

Final Phase

Start: April 30, 2050, midnight

Description: Final phase (no submission, your last submission from the previous phase is automatically forwarded).

Competition Ends

Never

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# Username Score
1 kimgerdes 0.3143
2 guyon 0.3143